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MMDF: Mobile Microscopy Deep Framework

2020-07-27 17:27:59
Anatasiia Kornilova, Mikhail Salnikov, Olga Novitskaya, Maria Begicheva, Egor Sevriugov, Kirill Shcherbakov
arXiv_CV
       
Abstract

In the last decade, a huge step was done in the field of mobile microscopes development as well as in the field of mobile microscopy application to real-life disease diagnostics and a lot of other important areas (air/water quality pollution, education, agriculture). In current study we applied image processing techniques from Deep Learning (in-focus/out-of-focus classification, image deblurring and denoising, multi-focus image fusion) to the data obtained from the mobile microscope. Overview of significant works for every task is presented, the most suitable approaches were highlighted. Chosen approaches were implemented as well as their performance were compared with classical computer vision techniques.

Abstract (translated)

URL

https://arxiv.org/abs/2007.13701

PDF

https://arxiv.org/pdf/2007.13701.pdf

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